Overview

Brought to you by YData

Dataset statistics

Number of variables24
Number of observations1177
Missing cells108
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory571.8 KiB
Average record size in memory497.5 B

Variable types

DateTime2
Categorical2
Numeric20

Alerts

cpc总费用 is highly overall correlated with cpc曝光量 and 8 other fieldsHigh correlation
cpc曝光量 is highly overall correlated with cpc总费用 and 8 other fieldsHigh correlation
cpc访问量 is highly overall correlated with cpc总费用 and 9 other fieldsHigh correlation
gmvroi is highly overall correlated with 下单转换率 and 1 other fieldsHigh correlation
下单转换率 is highly overall correlated with gmvroi and 1 other fieldsHigh correlation
单均gmv is highly overall correlated with 单均实收 and 3 other fieldsHigh correlation
单均实收 is highly overall correlated with 单均gmv and 1 other fieldsHigh correlation
实收roi is highly overall correlated with gmvroi and 3 other fieldsHigh correlation
平台i is highly overall correlated with 平台门店名称 and 1 other fieldsHigh correlation
平台门店名称 is highly overall correlated with 平台i and 1 other fieldsHigh correlation
有效订单 is highly overall correlated with cpc总费用 and 10 other fieldsHigh correlation
自增主键 is highly overall correlated with cpc访问量 and 1 other fieldsHigh correlation
自然曝光量 is highly overall correlated with 有效订单 and 6 other fieldsHigh correlation
自然访问量 is highly overall correlated with cpc总费用 and 9 other fieldsHigh correlation
门店ID is highly overall correlated with 平台i and 1 other fieldsHigh correlation
门店下单量 is highly overall correlated with cpc总费用 and 10 other fieldsHigh correlation
门店实收 is highly overall correlated with cpc总费用 and 9 other fieldsHigh correlation
门店曝光量 is highly overall correlated with cpc总费用 and 9 other fieldsHigh correlation
门店营业额 is highly overall correlated with cpc总费用 and 9 other fieldsHigh correlation
门店访问量 is highly overall correlated with cpc总费用 and 10 other fieldsHigh correlation
cpc单次点击费用 has 12 (1.0%) missing valuesMissing
自然曝光量 has 12 (1.0%) missing valuesMissing
自然访问量 has 12 (1.0%) missing valuesMissing
门店下单量 has 12 (1.0%) missing valuesMissing
门店曝光量 has 12 (1.0%) missing valuesMissing
门店访问量 has 12 (1.0%) missing valuesMissing
gmvroi is highly skewed (γ1 = 31.91391675)Skewed
实收roi is highly skewed (γ1 = 31.32709453)Skewed
自增主键 has unique valuesUnique
cpc总费用 has 12 (1.0%) zerosZeros
cpc访问量 has 12 (1.0%) zerosZeros
gmvroi has 22 (1.9%) zerosZeros
下单转换率 has 13 (1.1%) zerosZeros
实收roi has 22 (1.9%) zerosZeros
无效订单 has 781 (66.4%) zerosZeros

Reproduction

Analysis started2025-11-04 07:01:35.330629
Analysis finished2025-11-04 07:01:50.484356
Duration15.15 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

Distinct374
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
Minimum2019-12-12 11:54:00
Maximum2020-09-26 14:20:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-04T15:01:50.544270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.593803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

平台i
Categorical

High correlation 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size92.2 KiB
饿了么
731 
美团
446 

Length

Max length3
Median length3
Mean length2.6210705
Min length2

Characters and Unicode

Total characters3085
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row美团
2nd row美团
3rd row美团
4th row美团
5th row饿了么

Common Values

ValueCountFrequency (%)
饿了么731
62.1%
美团446
37.9%

Length

2025-11-04T15:01:50.632616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-04T15:01:50.660416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
饿了么731
62.1%
美团446
37.9%

Most occurring characters

ValueCountFrequency (%)
饿731
23.7%
731
23.7%
731
23.7%
446
14.5%
446
14.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)3085
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
饿731
23.7%
731
23.7%
731
23.7%
446
14.5%
446
14.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3085
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
饿731
23.7%
731
23.7%
731
23.7%
446
14.5%
446
14.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3085
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
饿731
23.7%
731
23.7%
731
23.7%
446
14.5%
446
14.5%

门店ID
Real number (ℝ)

High correlation 

Distinct18
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1027077 × 109
Minimum8052557
Maximum2.001573 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:50.684390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum8052557
5-th percentile8106681
Q18491999
median2.0005071 × 109
Q32.0011044 × 109
95-th percentile2.001221 × 109
Maximum2.001573 × 109
Range1.9935204 × 109
Interquartile range (IQR)1.9926124 × 109

Descriptive statistics

Standard deviation9.681788 × 108
Coefficient of variation (CV)0.87800129
Kurtosis-1.9519444
Mean1.1027077 × 109
Median Absolute Deviation (MAD)713877
Skewness-0.1634554
Sum1.297887 × 1012
Variance9.3737018 × 1017
MonotonicityNot monotonic
2025-11-04T15:01:50.716508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2001104355271
23.0%
8491999191
16.2%
2000507076110
9.3%
200055579288
 
7.5%
33746013685
 
7.2%
200122095368
 
5.8%
200102001964
 
5.4%
816584261
 
5.2%
818459048
 
4.1%
805255740
 
3.4%
Other values (8)151
12.8%
ValueCountFrequency (%)
805255740
 
3.4%
810668131
 
2.6%
816584261
 
5.2%
818459048
 
4.1%
822318420
 
1.7%
826033129
 
2.5%
8491999191
16.2%
942811026
 
2.2%
30522534516
 
1.4%
33746013685
7.2%
ValueCountFrequency (%)
20015729922
 
0.2%
200122095368
 
5.8%
2001104355271
23.0%
200105369918
 
1.5%
20010425529
 
0.8%
200102001964
 
5.4%
200055579288
 
7.5%
2000507076110
9.3%
33746013685
 
7.2%
30522534516
 
1.4%

平台门店名称
Categorical

High correlation 

Distinct31
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size154.7 KiB
蛙小辣火锅杯(宝山店)
191 
蛙小辣·美蛙火锅杯麻辣烫(宝山店)
164 
蛙小辣·美蛙火锅杯(宝山店)
107 
蛙小辣·美蛙火锅杯(虹口足球场店)
88 
拌客·干拌麻辣烫(武宁路店)
83 
Other values (26)
544 

Length

Max length18
Median length17
Mean length14.100255
Min length6

Characters and Unicode

Total characters16596
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row蛙小辣火锅杯(合生汇店)
2nd row蛙小辣美蛙火锅杯(大宁国际店)
3rd row蛙小辣·美蛙火锅杯(长风大悦城店)
4th row蛙小辣·美蛙火锅杯(虹口足球场店)
5th row利芳·一人食大盘鸡(国定路店)

Common Values

ValueCountFrequency (%)
蛙小辣火锅杯(宝山店)191
16.2%
蛙小辣·美蛙火锅杯麻辣烫(宝山店)164
13.9%
蛙小辣·美蛙火锅杯(宝山店)107
 
9.1%
蛙小辣·美蛙火锅杯(虹口足球场店)88
 
7.5%
拌客·干拌麻辣烫(武宁路店)83
 
7.1%
蛙小辣火锅杯(五角场店)76
 
6.5%
蛙小辣·美蛙火锅杯(真如店)58
 
4.9%
蛙小辣·美蛙火锅杯(虹口足球场店)55
 
4.7%
利芳·一人食大盘鸡(国定路店)44
 
3.7%
蛙小辣火锅杯(合生汇店)34
 
2.9%
Other values (21)277
23.5%

Length

2025-11-04T15:01:50.753577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
蛙小辣火锅杯(宝山店)191
16.2%
蛙小辣·美蛙火锅杯麻辣烫(宝山店164
13.9%
蛙小辣·美蛙火锅杯(宝山店107
 
9.1%
蛙小辣·美蛙火锅杯(虹口足球场店88
 
7.5%
拌客·干拌麻辣烫(武宁路店83
 
7.1%
蛙小辣火锅杯(五角场店76
 
6.5%
蛙小辣·美蛙火锅杯(真如店58
 
4.9%
蛙小辣·美蛙火锅杯(虹口足球场店)55
 
4.7%
利芳·一人食大盘鸡(国定路店44
 
3.7%
蛙小辣火锅杯(合生汇店)34
 
2.9%
Other values (21)277
23.5%

Most occurring characters

ValueCountFrequency (%)
1612
 
9.7%
1289
 
7.8%
1171
 
7.1%
998
 
6.0%
998
 
6.0%
998
 
6.0%
998
 
6.0%
(726
 
4.4%
)726
 
4.4%
·682
 
4.1%
Other values (48)6398
38.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)16596
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1612
 
9.7%
1289
 
7.8%
1171
 
7.1%
998
 
6.0%
998
 
6.0%
998
 
6.0%
998
 
6.0%
(726
 
4.4%
)726
 
4.4%
·682
 
4.1%
Other values (48)6398
38.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)16596
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1612
 
9.7%
1289
 
7.8%
1171
 
7.1%
998
 
6.0%
998
 
6.0%
998
 
6.0%
998
 
6.0%
(726
 
4.4%
)726
 
4.4%
·682
 
4.1%
Other values (48)6398
38.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)16596
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1612
 
9.7%
1289
 
7.8%
1171
 
7.1%
998
 
6.0%
998
 
6.0%
998
 
6.0%
998
 
6.0%
(726
 
4.4%
)726
 
4.4%
·682
 
4.1%
Other values (48)6398
38.6%

日期
Date

Distinct315
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
Minimum2019-10-28 00:00:00
Maximum2020-09-25 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-04T15:01:50.788888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.831255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

cpc单次点击费用
Real number (ℝ)

Missing 

Distinct166
Distinct (%)14.2%
Missing12
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean1.3896223
Minimum0.02
Maximum2.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:50.873827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.892
Q11.24
median1.38
Q31.54
95-th percentile1.96
Maximum2.98
Range2.96
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.30395027
Coefficient of variation (CV)0.21872869
Kurtosis2.0768236
Mean1.3896223
Median Absolute Deviation (MAD)0.15
Skewness0.21229082
Sum1618.91
Variance0.092385768
MonotonicityNot monotonic
2025-11-04T15:01:50.917738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.435
 
3.0%
1.3931
 
2.6%
1.3829
 
2.5%
1.4327
 
2.3%
1.3126
 
2.2%
1.3326
 
2.2%
1.3223
 
2.0%
1.4122
 
1.9%
1.2822
 
1.9%
1.3421
 
1.8%
Other values (156)903
76.7%
ValueCountFrequency (%)
0.021
 
0.1%
0.271
 
0.1%
0.442
0.2%
0.511
 
0.1%
0.561
 
0.1%
0.584
0.3%
0.592
0.2%
0.613
0.3%
0.621
 
0.1%
0.631
 
0.1%
ValueCountFrequency (%)
2.981
 
0.1%
2.51
 
0.1%
2.471
 
0.1%
2.341
 
0.1%
2.31
 
0.1%
2.281
 
0.1%
2.271
 
0.1%
2.261
 
0.1%
2.253
0.3%
2.242
0.2%

cpc总费用
Real number (ℝ)

High correlation  Zeros 

Distinct1017
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.58017
Minimum0
Maximum846.4
Zeros12
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:50.958944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.544
Q139.91
median76.2
Q3190
95-th percentile416.972
Maximum846.4
Range846.4
Interquartile range (IQR)150.09

Descriptive statistics

Standard deviation134.53922
Coefficient of variation (CV)1.0382701
Kurtosis5.3166983
Mean129.58017
Median Absolute Deviation (MAD)51
Skewness2.0911377
Sum152515.86
Variance18100.802
MonotonicityNot monotonic
2025-11-04T15:01:50.997026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5030
 
2.5%
8015
 
1.3%
012
 
1.0%
1009
 
0.8%
608
 
0.7%
3008
 
0.7%
1505
 
0.4%
4005
 
0.4%
2504
 
0.3%
29.93
 
0.3%
Other values (1007)1078
91.6%
ValueCountFrequency (%)
012
1.0%
0.021
 
0.1%
0.441
 
0.1%
0.941
 
0.1%
11
 
0.1%
1.11
 
0.1%
1.281
 
0.1%
1.32
 
0.2%
1.42
 
0.2%
21
 
0.1%
ValueCountFrequency (%)
846.41
 
0.1%
8001
 
0.1%
768.151
 
0.1%
762.81
 
0.1%
757.951
 
0.1%
7002
0.2%
699.72
0.2%
699.61
 
0.1%
699.43
0.3%
699.11
 
0.1%

cpc曝光量
Real number (ℝ)

High correlation 

Distinct944
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1350.9864
Minimum0
Maximum7812
Zeros8
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.100647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile145.6
Q1466
median863
Q31950
95-th percentile3822
Maximum7812
Range7812
Interquartile range (IQR)1484

Descriptive statistics

Standard deviation1256.423
Coefficient of variation (CV)0.93000417
Kurtosis3.5180955
Mean1350.9864
Median Absolute Deviation (MAD)536
Skewness1.7148962
Sum1590111
Variance1578598.7
MonotonicityNot monotonic
2025-11-04T15:01:51.143821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08
 
0.7%
16
 
0.5%
6404
 
0.3%
6504
 
0.3%
5214
 
0.3%
3624
 
0.3%
3274
 
0.3%
3494
 
0.3%
6173
 
0.3%
5243
 
0.3%
Other values (934)1133
96.3%
ValueCountFrequency (%)
08
0.7%
16
0.5%
23
 
0.3%
32
 
0.2%
41
 
0.1%
51
 
0.1%
72
 
0.2%
82
 
0.2%
121
 
0.1%
171
 
0.1%
ValueCountFrequency (%)
78121
0.1%
74811
0.1%
74661
0.1%
71781
0.1%
69411
0.1%
67101
0.1%
61981
0.1%
61431
0.1%
61191
0.1%
59641
0.1%

cpc访问量
Real number (ℝ)

High correlation  Zeros 

Distinct291
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.31096
Minimum0
Maximum502
Zeros12
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.185514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q129
median57
Q3133
95-th percentile260.6
Maximum502
Range502
Interquartile range (IQR)104

Descriptive statistics

Standard deviation87.907575
Coefficient of variation (CV)0.96272752
Kurtosis3.6060928
Mean91.31096
Median Absolute Deviation (MAD)36
Skewness1.7762244
Sum107473
Variance7727.7417
MonotonicityNot monotonic
2025-11-04T15:01:51.226851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2725
 
2.1%
3220
 
1.7%
2518
 
1.5%
2618
 
1.5%
2117
 
1.4%
1717
 
1.4%
3417
 
1.4%
3316
 
1.4%
2916
 
1.4%
3516
 
1.4%
Other values (281)997
84.7%
ValueCountFrequency (%)
012
1.0%
110
0.8%
25
0.4%
32
 
0.2%
44
 
0.3%
57
0.6%
63
 
0.3%
74
 
0.3%
84
 
0.3%
95
0.4%
ValueCountFrequency (%)
5021
0.1%
4991
0.1%
4891
0.1%
4791
0.1%
4651
0.1%
4571
0.1%
4371
0.1%
4331
0.1%
4301
0.1%
4271
0.1%

gmvroi
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct699
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5499065
Minimum0
Maximum534.66
Zeros22
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.265950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.408
Q16.04
median7.59
Q39.85
95-th percentile14.592
Maximum534.66
Range534.66
Interquartile range (IQR)3.81

Descriptive statistics

Standard deviation15.723512
Coefficient of variation (CV)1.8390274
Kurtosis1068.3177
Mean8.5499065
Median Absolute Deviation (MAD)1.84
Skewness31.913917
Sum10063.24
Variance247.22884
MonotonicityNot monotonic
2025-11-04T15:01:51.305250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
022
 
1.9%
6.067
 
0.6%
9.187
 
0.6%
7.365
 
0.4%
5.235
 
0.4%
8.575
 
0.4%
6.565
 
0.4%
6.65
 
0.4%
6.325
 
0.4%
10.885
 
0.4%
Other values (689)1106
94.0%
ValueCountFrequency (%)
022
1.9%
2.061
 
0.1%
2.241
 
0.1%
2.281
 
0.1%
2.321
 
0.1%
2.421
 
0.1%
2.481
 
0.1%
2.511
 
0.1%
2.752
 
0.2%
2.791
 
0.1%
ValueCountFrequency (%)
534.661
0.1%
28.761
0.1%
24.21
0.1%
22.761
0.1%
22.321
0.1%
20.711
0.1%
20.241
0.1%
20.171
0.1%
20.131
0.1%
18.41
0.1%

下单转换率
Real number (ℝ)

High correlation  Zeros 

Distinct36
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18851317
Minimum0
Maximum0.42
Zeros13
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.340540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.09
Q10.15
median0.19
Q30.23
95-th percentile0.29
Maximum0.42
Range0.42
Interquartile range (IQR)0.08

Descriptive statistics

Standard deviation0.063103535
Coefficient of variation (CV)0.33474338
Kurtosis0.31726042
Mean0.18851317
Median Absolute Deviation (MAD)0.04
Skewness0.043805661
Sum221.88
Variance0.0039820562
MonotonicityNot monotonic
2025-11-04T15:01:51.375454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.1886
 
7.3%
0.1576
 
6.5%
0.2173
 
6.2%
0.1473
 
6.2%
0.1772
 
6.1%
0.1970
 
5.9%
0.268
 
5.8%
0.2358
 
4.9%
0.1656
 
4.8%
0.2256
 
4.8%
Other values (26)489
41.5%
ValueCountFrequency (%)
013
 
1.1%
0.042
 
0.2%
0.054
 
0.3%
0.063
 
0.3%
0.0711
 
0.9%
0.0818
 
1.5%
0.0918
 
1.5%
0.119
 
1.6%
0.1130
2.5%
0.1248
4.1%
ValueCountFrequency (%)
0.421
 
0.1%
0.383
 
0.3%
0.363
 
0.3%
0.351
 
0.1%
0.345
 
0.4%
0.337
 
0.6%
0.329
 
0.8%
0.3110
0.8%
0.319
1.6%
0.2923
2.0%

单均gmv
Real number (ℝ)

High correlation 

Distinct943
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.694299
Minimum0
Maximum90.76
Zeros9
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.413389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile45.632
Q152.99
median57.81
Q362.74
95-th percentile71.372
Maximum90.76
Range90.76
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation9.2282739
Coefficient of variation (CV)0.15995123
Kurtosis10.526872
Mean57.694299
Median Absolute Deviation (MAD)4.89
Skewness-1.5984278
Sum67906.19
Variance85.161038
MonotonicityNot monotonic
2025-11-04T15:01:51.451945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09
 
0.8%
52.845
 
0.4%
68.774
 
0.3%
51.643
 
0.3%
54.13
 
0.3%
52.783
 
0.3%
59.763
 
0.3%
58.663
 
0.3%
54.23
 
0.3%
63.913
 
0.3%
Other values (933)1138
96.7%
ValueCountFrequency (%)
09
0.8%
32.81
 
0.1%
37.111
 
0.1%
38.561
 
0.1%
38.711
 
0.1%
391
 
0.1%
39.361
 
0.1%
39.391
 
0.1%
39.771
 
0.1%
39.881
 
0.1%
ValueCountFrequency (%)
90.761
0.1%
86.881
0.1%
85.271
0.1%
85.171
0.1%
84.621
0.1%
81.211
0.1%
80.631
0.1%
80.221
0.1%
79.971
0.1%
79.361
0.1%

单均实收
Real number (ℝ)

High correlation 

Distinct844
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.699456
Minimum0
Maximum47.32
Zeros9
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.489337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.732
Q117.82
median20.53
Q323.53
95-th percentile28.692
Maximum47.32
Range47.32
Interquartile range (IQR)5.71

Descriptive statistics

Standard deviation5.2444284
Coefficient of variation (CV)0.25336068
Kurtosis3.204278
Mean20.699456
Median Absolute Deviation (MAD)2.87
Skewness-0.14951894
Sum24363.26
Variance27.504029
MonotonicityNot monotonic
2025-11-04T15:01:51.528417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09
 
0.8%
20.657
 
0.6%
22.045
 
0.4%
19.84
 
0.3%
19.174
 
0.3%
20.514
 
0.3%
18.244
 
0.3%
20.34
 
0.3%
19.424
 
0.3%
24.074
 
0.3%
Other values (834)1128
95.8%
ValueCountFrequency (%)
09
0.8%
3.041
 
0.1%
3.61
 
0.1%
3.721
 
0.1%
3.751
 
0.1%
3.81
 
0.1%
4.151
 
0.1%
4.21
 
0.1%
4.341
 
0.1%
4.421
 
0.1%
ValueCountFrequency (%)
47.321
0.1%
40.011
0.1%
39.811
0.1%
39.591
0.1%
38.721
0.1%
38.261
0.1%
38.071
0.1%
37.242
0.2%
371
0.1%
35.691
0.1%

实收roi
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct433
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0534579
Minimum0
Maximum189.32
Zeros22
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.565526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.148
Q12.02
median2.66
Q33.6
95-th percentile5.26
Maximum189.32
Range189.32
Interquartile range (IQR)1.58

Descriptive statistics

Standard deviation5.6018115
Coefficient of variation (CV)1.8345795
Kurtosis1041.8185
Mean3.0534579
Median Absolute Deviation (MAD)0.75
Skewness31.327095
Sum3593.92
Variance31.380292
MonotonicityNot monotonic
2025-11-04T15:01:51.604620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
022
 
1.9%
2.9611
 
0.9%
1.9610
 
0.8%
2.549
 
0.8%
1.739
 
0.8%
2.678
 
0.7%
2.388
 
0.7%
3.188
 
0.7%
3.328
 
0.7%
2.187
 
0.6%
Other values (423)1077
91.5%
ValueCountFrequency (%)
022
1.9%
0.271
 
0.1%
0.551
 
0.1%
0.572
 
0.2%
0.581
 
0.1%
0.611
 
0.1%
0.641
 
0.1%
0.691
 
0.1%
0.721
 
0.1%
0.751
 
0.1%
ValueCountFrequency (%)
189.321
0.1%
13.281
0.1%
10.51
0.1%
9.371
0.1%
8.371
0.1%
8.231
0.1%
7.871
0.1%
7.791
0.1%
7.781
0.1%
7.141
0.1%

无效订单
Real number (ℝ)

Zeros 

Distinct12
Distinct (%)1.0%
Missing9
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.6010274
Minimum0
Maximum12
Zeros781
Zeros (%)66.4%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.635232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1883751
Coefficient of variation (CV)1.9772395
Kurtosis19.926246
Mean0.6010274
Median Absolute Deviation (MAD)0
Skewness3.5734738
Sum702
Variance1.4122354
MonotonicityNot monotonic
2025-11-04T15:01:51.662760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0781
66.4%
1231
 
19.6%
281
 
6.9%
338
 
3.2%
418
 
1.5%
510
 
0.8%
63
 
0.3%
72
 
0.2%
121
 
0.1%
101
 
0.1%
Other values (2)2
 
0.2%
(Missing)9
 
0.8%
ValueCountFrequency (%)
0781
66.4%
1231
 
19.6%
281
 
6.9%
338
 
3.2%
418
 
1.5%
510
 
0.8%
63
 
0.3%
72
 
0.2%
81
 
0.1%
101
 
0.1%
ValueCountFrequency (%)
121
 
0.1%
111
 
0.1%
101
 
0.1%
81
 
0.1%
72
 
0.2%
63
 
0.3%
510
 
0.8%
418
 
1.5%
338
3.2%
281
6.9%

有效订单
Real number (ℝ)

High correlation 

Distinct145
Distinct (%)12.4%
Missing9
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean41.988014
Minimum4
Maximum232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.699222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.35
Q117
median26
Q361.25
95-th percentile111
Maximum232
Range228
Interquartile range (IQR)44.25

Descriptive statistics

Standard deviation35.579085
Coefficient of variation (CV)0.84736291
Kurtosis3.7589166
Mean41.988014
Median Absolute Deviation (MAD)14
Skewness1.7601322
Sum49042
Variance1265.8713
MonotonicityNot monotonic
2025-11-04T15:01:51.745739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1956
 
4.8%
1552
 
4.4%
1842
 
3.6%
1740
 
3.4%
1235
 
3.0%
1635
 
3.0%
2131
 
2.6%
2231
 
2.6%
2029
 
2.5%
1127
 
2.3%
Other values (135)790
67.1%
ValueCountFrequency (%)
45
 
0.4%
58
 
0.7%
66
 
0.5%
79
 
0.8%
815
1.3%
916
1.4%
1017
1.4%
1127
2.3%
1235
3.0%
1324
2.0%
ValueCountFrequency (%)
2321
0.1%
2072
0.2%
2011
0.1%
1981
0.1%
1951
0.1%
1911
0.1%
1891
0.1%
1861
0.1%
1812
0.2%
1751
0.1%

自增主键
Real number (ℝ)

High correlation  Unique 

Distinct1177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3023888.6
Minimum1501603
Maximum7684897
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:51.844148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1501603
5-th percentile1516524.2
Q11872058
median2538079
Q33775030
95-th percentile6103567.8
Maximum7684897
Range6183294
Interquartile range (IQR)1902972

Descriptive statistics

Standard deviation1433359.6
Coefficient of variation (CV)0.47401205
Kurtosis0.68880151
Mean3023888.6
Median Absolute Deviation (MAD)830976
Skewness1.1639821
Sum3.5591169 × 109
Variance2.0545198 × 1012
MonotonicityNot monotonic
2025-11-04T15:01:51.883652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15016031
 
0.1%
31772881
 
0.1%
32611911
 
0.1%
32482371
 
0.1%
32480331
 
0.1%
32352641
 
0.1%
32347191
 
0.1%
32345051
 
0.1%
32206871
 
0.1%
32200271
 
0.1%
Other values (1167)1167
99.2%
ValueCountFrequency (%)
15016031
0.1%
15016051
0.1%
15022651
0.1%
15022741
0.1%
15025231
0.1%
15027061
0.1%
15027361
0.1%
15029671
0.1%
15029871
0.1%
15036541
0.1%
ValueCountFrequency (%)
76848971
0.1%
76276501
0.1%
75256841
0.1%
75218311
0.1%
74618251
0.1%
74580341
0.1%
74036041
0.1%
74001001
0.1%
73488331
0.1%
73466421
0.1%

自然曝光量
Real number (ℝ)

High correlation  Missing 

Distinct919
Distinct (%)78.9%
Missing12
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean1245.3133
Minimum-5534
Maximum7153
Zeros0
Zeros (%)0.0%
Negative12
Negative (%)1.0%
Memory size9.3 KiB
2025-11-04T15:01:51.926740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-5534
5-th percentile213
Q1492
median812
Q31599
95-th percentile3709.2
Maximum7153
Range12687
Interquartile range (IQR)1107

Descriptive statistics

Standard deviation1206.3636
Coefficient of variation (CV)0.96872297
Kurtosis5.3627132
Mean1245.3133
Median Absolute Deviation (MAD)430
Skewness1.8383567
Sum1450790
Variance1455313.1
MonotonicityNot monotonic
2025-11-04T15:01:51.969914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6746
 
0.5%
4096
 
0.5%
5355
 
0.4%
4634
 
0.3%
4394
 
0.3%
5174
 
0.3%
4954
 
0.3%
3244
 
0.3%
5884
 
0.3%
2674
 
0.3%
Other values (909)1120
95.2%
(Missing)12
 
1.0%
ValueCountFrequency (%)
-55341
0.1%
-3431
0.1%
-2491
0.1%
-2371
0.1%
-2361
0.1%
-2211
0.1%
-2141
0.1%
-1681
0.1%
-1341
0.1%
-1121
0.1%
ValueCountFrequency (%)
71531
0.1%
70031
0.1%
68981
0.1%
67071
0.1%
66791
0.1%
66161
0.1%
65251
0.1%
64411
0.1%
64061
0.1%
61291
0.1%

自然访问量
Real number (ℝ)

High correlation  Missing 

Distinct314
Distinct (%)27.0%
Missing12
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean124.75021
Minimum-427
Maximum745
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)0.1%
Memory size9.3 KiB
2025-11-04T15:01:52.013198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-427
5-th percentile34
Q150
median92
Q3169
95-th percentile328
Maximum745
Range1172
Interquartile range (IQR)119

Descriptive statistics

Standard deviation101.60768
Coefficient of variation (CV)0.81448902
Kurtosis3.5821943
Mean124.75021
Median Absolute Deviation (MAD)48
Skewness1.4541109
Sum145334
Variance10324.121
MonotonicityNot monotonic
2025-11-04T15:01:52.066660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4824
 
2.0%
4621
 
1.8%
4221
 
1.8%
5218
 
1.5%
4118
 
1.5%
4917
 
1.4%
4716
 
1.4%
4316
 
1.4%
5015
 
1.3%
3915
 
1.3%
Other values (304)984
83.6%
ValueCountFrequency (%)
-4271
 
0.1%
142
0.2%
151
 
0.1%
192
0.2%
211
 
0.1%
222
0.2%
231
 
0.1%
241
 
0.1%
251
 
0.1%
264
0.3%
ValueCountFrequency (%)
7451
0.1%
5511
0.1%
5321
0.1%
5301
0.1%
5281
0.1%
4951
0.1%
4891
0.1%
4821
0.1%
4801
0.1%
4761
0.1%

门店下单量
Real number (ℝ)

High correlation  Missing 

Distinct147
Distinct (%)12.6%
Missing12
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean40.893562
Minimum0
Maximum224
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:52.107350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q117
median26
Q360
95-th percentile108
Maximum224
Range224
Interquartile range (IQR)43

Descriptive statistics

Standard deviation34.50072
Coefficient of variation (CV)0.84367117
Kurtosis3.5519811
Mean40.893562
Median Absolute Deviation (MAD)14
Skewness1.7177411
Sum47641
Variance1190.2997
MonotonicityNot monotonic
2025-11-04T15:01:52.147424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1851
 
4.3%
1551
 
4.3%
1945
 
3.8%
1745
 
3.8%
1233
 
2.8%
2033
 
2.8%
1631
 
2.6%
1430
 
2.5%
1130
 
2.5%
2130
 
2.5%
Other values (137)786
66.8%
ValueCountFrequency (%)
01
 
0.1%
44
 
0.3%
58
 
0.7%
68
 
0.7%
710
 
0.8%
815
1.3%
921
1.8%
1017
1.4%
1130
2.5%
1233
2.8%
ValueCountFrequency (%)
2241
0.1%
2012
0.2%
1931
0.1%
1911
0.1%
1901
0.1%
1861
0.1%
1821
0.1%
1751
0.1%
1741
0.1%
1691
0.1%

门店实收
Real number (ℝ)

High correlation 

Distinct1152
Distinct (%)98.6%
Missing9
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean789.76272
Minimum30
Maximum3780.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:52.185648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile204.361
Q1375.595
median587.645
Q31100.1525
95-th percentile1911.885
Maximum3780.11
Range3750.11
Interquartile range (IQR)724.5575

Descriptive statistics

Standard deviation566.84093
Coefficient of variation (CV)0.71773573
Kurtosis2.1247577
Mean789.76272
Median Absolute Deviation (MAD)280.6
Skewness1.3913883
Sum922442.86
Variance321308.64
MonotonicityNot monotonic
2025-11-04T15:01:52.227231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14312
 
0.2%
357.042
 
0.2%
256.652
 
0.2%
15982
 
0.2%
13762
 
0.2%
10732
 
0.2%
10802
 
0.2%
5142
 
0.2%
2952
 
0.2%
11002
 
0.2%
Other values (1142)1148
97.5%
(Missing)9
 
0.8%
ValueCountFrequency (%)
301
0.1%
661
0.1%
66.161
0.1%
671
0.1%
76.351
0.1%
811
0.1%
851
0.1%
871
0.1%
88.41
0.1%
99.851
0.1%
ValueCountFrequency (%)
3780.111
0.1%
3367.761
0.1%
3271.861
0.1%
3171.211
0.1%
2993.951
0.1%
2992.131
0.1%
2849.171
0.1%
2815.731
0.1%
2789.791
0.1%
27571
0.1%

门店曝光量
Real number (ℝ)

High correlation  Missing 

Distinct1031
Distinct (%)88.5%
Missing12
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean2604.0815
Minimum0
Maximum11066
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:52.268578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile774.2
Q11123
median2016
Q33605
95-th percentile6257.2
Maximum11066
Range11066
Interquartile range (IQR)2482

Descriptive statistics

Standard deviation1813.4936
Coefficient of variation (CV)0.69640429
Kurtosis1.451585
Mean2604.0815
Median Absolute Deviation (MAD)1063
Skewness1.2303817
Sum3033755
Variance3288758.9
MonotonicityNot monotonic
2025-11-04T15:01:52.309454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13254
 
0.3%
8553
 
0.3%
10743
 
0.3%
8873
 
0.3%
10353
 
0.3%
11123
 
0.3%
11353
 
0.3%
12243
 
0.3%
11223
 
0.3%
10003
 
0.3%
Other values (1021)1134
96.3%
(Missing)12
 
1.0%
ValueCountFrequency (%)
01
0.1%
3101
0.1%
3971
0.1%
5141
0.1%
5191
0.1%
5231
0.1%
5321
0.1%
5341
0.1%
5391
0.1%
5461
0.1%
ValueCountFrequency (%)
110661
0.1%
106211
0.1%
102381
0.1%
100381
0.1%
97081
0.1%
91081
0.1%
89761
0.1%
89171
0.1%
87121
0.1%
85831
0.1%

门店营业额
Real number (ℝ)

High correlation 

Distinct1165
Distinct (%)99.7%
Missing9
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean2298.8169
Minimum164
Maximum11012.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:52.349116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum164
5-th percentile585.465
Q11040.5175
median1609.425
Q33296.95
95-th percentile5632.85
Maximum11012.76
Range10848.76
Interquartile range (IQR)2256.4325

Descriptive statistics

Standard deviation1728.3866
Coefficient of variation (CV)0.7518592
Kurtosis2.1479114
Mean2298.8169
Median Absolute Deviation (MAD)810.095
Skewness1.4305758
Sum2685018.2
Variance2987320.4
MonotonicityNot monotonic
2025-11-04T15:01:52.389036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55452
 
0.2%
29542
 
0.2%
10852
 
0.2%
3391.381
 
0.1%
1216.561
 
0.1%
500.941
 
0.1%
753.971
 
0.1%
1838.311
 
0.1%
754.71
 
0.1%
1547.391
 
0.1%
Other values (1155)1155
98.1%
(Missing)9
 
0.8%
ValueCountFrequency (%)
1641
0.1%
1811
0.1%
199.981
0.1%
2271
0.1%
2441
0.1%
244.161
0.1%
288.111
0.1%
299.621
0.1%
3051
0.1%
311.941
0.1%
ValueCountFrequency (%)
11012.761
0.1%
9614.51
0.1%
9423.761
0.1%
9230.541
0.1%
91491
0.1%
8992.481
0.1%
8847.581
0.1%
86661
0.1%
86331
0.1%
8589.31
0.1%

门店访问量
Real number (ℝ)

High correlation  Missing 

Distinct440
Distinct (%)37.8%
Missing12
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean216.70129
Minimum0
Maximum985
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2025-11-04T15:01:52.430500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile58
Q186
median157
Q3314
95-th percentile547
Maximum985
Range985
Interquartile range (IQR)228

Descriptive statistics

Standard deviation161.65603
Coefficient of variation (CV)0.74598558
Kurtosis1.204818
Mean216.70129
Median Absolute Deviation (MAD)86
Skewness1.2235964
Sum252457
Variance26132.674
MonotonicityNot monotonic
2025-11-04T15:01:52.471303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7419
 
1.6%
6313
 
1.1%
9313
 
1.1%
8611
 
0.9%
7111
 
0.9%
7610
 
0.8%
8910
 
0.8%
6010
 
0.8%
7710
 
0.8%
7210
 
0.8%
Other values (430)1048
89.0%
(Missing)12
 
1.0%
ValueCountFrequency (%)
01
 
0.1%
311
 
0.1%
352
0.2%
392
0.2%
401
 
0.1%
411
 
0.1%
434
0.3%
444
0.3%
451
 
0.1%
462
0.2%
ValueCountFrequency (%)
9851
0.1%
8711
0.1%
7981
0.1%
7881
0.1%
7421
0.1%
7271
0.1%
7261
0.1%
7231
0.1%
7221
0.1%
7181
0.1%

Interactions

2025-11-04T15:01:49.518364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:35.840281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.596083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.348263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.021178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.991921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.758009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.514832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.205626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.860462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.569537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.247971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.993346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.624629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.357430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.038900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.724184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.411178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.125477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.844554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.553538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:35.891961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.634485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.382260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.066307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.033139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.794596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.560120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.245928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.894629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.608321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.284220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.027750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.659443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.394862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.073892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.757358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.446930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.162749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.879443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.593358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:35.928120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.667436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.413139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.106596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.073334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.829572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.595144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.280244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.925450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.644350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.320359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.058684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.691591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.428683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.108833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.857530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.481528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.196248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.913432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.623083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:35.961676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.699212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.441376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.151248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.111254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.859857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.626840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.310885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.955312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.677880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.350839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.088272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.721802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.460802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.139328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.887494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.514248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.228256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.943715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.657227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:35.997755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.733687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.473493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.202390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.175967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.893197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.661493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.344603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.989958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.713327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.386550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.120991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.756209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.496552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.176508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.921045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.551132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.261144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.978244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.689717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.033533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.765585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.508957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.245603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.211078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.945020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.693682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.378969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.020447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.746935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.417796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.153045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.786853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.531350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.208455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.950788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.583929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.353205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.009108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.722740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.070547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.796208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.550982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.280841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.247174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.977451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.729845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.409492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.114409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.779956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.449374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.190504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.822217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.563383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.240141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.981074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.617853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.384941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.041458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.756729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.126972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.830313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.587640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.315908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.283861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.020795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.760283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.438631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.144811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.812025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.480625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.219882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.859073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.596025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.271470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.010727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.650148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.417287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.073306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.792643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.159606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.867022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.619953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.350769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.318416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.058499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.789807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.468370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.173733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.844600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.518558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.251606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.891047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.630303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.304331image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.042661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.684030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.449020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.106509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.825758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.193372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.901349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.651119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.386275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.350847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.089362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.819701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.497385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.201854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.878156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.549559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.280238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.920570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.660648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.335973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.070982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.714669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.478887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.137488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.861714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.228078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.937430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.684994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.424908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.387948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.123236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.852028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.530135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.235028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.912462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.582364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.312797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.954157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.694969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.371389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.104064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.756806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.511718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.170439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.896012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.263605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.044761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.717187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.467866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.424191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.154888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.884228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.563623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.265254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.945670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.676390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.343957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.986153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.728984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.405075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.135961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.790336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.543958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.202963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.925741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.297162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.081658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.746782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.516082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.464401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.185746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.913941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.597953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.295129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.977233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.707138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.374070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.016088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.761127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.436376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.164773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.823251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.574032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.233089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.960579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.332952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.116751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.775828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.655618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.506364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.216522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.946224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.629531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.324886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.009319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.744244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.405402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.047438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.793397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.469406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.195099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.856072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.617645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.266616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.057705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.368350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.152246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.808087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.705690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.554450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.251746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.981043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.663402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.356418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.043415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.777393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.437531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.080443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.826717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.502290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.225512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.892182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.652928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.325115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.089808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.403904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.188617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.837739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.753187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.590676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.283879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.038258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.696069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.387455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.076990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.810477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.469784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.113336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.859135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.535497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.256782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.929248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.687172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.360631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.119210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.440575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.219477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.867192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.798089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.624227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.313173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.071129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.726298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.416046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.110840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.840684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.498480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.143474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.891232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.566845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.285563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.985446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.717743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.391481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.153040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.483461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.252837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.898899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.853367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.660448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.411987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.105670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.761440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.471446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.146079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.875159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.531116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.237146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.937789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.602529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.319734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.022271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.750091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.424547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.184525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.520917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.283974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.930938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.894987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.693352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.444991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.140577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.795029image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.501708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.179708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.906435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.561713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.276730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.972761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.642200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.349593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.059721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.780808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.455937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:50.216243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:36.558936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.316869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:37.987297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:38.938599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:39.726635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:40.479885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.173541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:41.828567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:42.532679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.212146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:43.961979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:44.593732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:45.325683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.005870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:46.674644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:47.380034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.092638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:48.811812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-04T15:01:49.486345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-11-04T15:01:52.510964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
cpc单次点击费用cpc总费用cpc曝光量cpc访问量gmvroi下单转换率单均gmv单均实收实收roi平台i平台门店名称无效订单有效订单自增主键自然曝光量自然访问量门店ID门店下单量门店实收门店曝光量门店营业额门店访问量
cpc单次点击费用1.0000.2390.1270.044-0.4640.188-0.285-0.281-0.4870.1230.3400.0590.0360.213-0.099-0.070-0.0190.046-0.0440.004-0.013-0.050
cpc总费用0.2391.0000.9520.971-0.391-0.139-0.431-0.318-0.4010.2300.3690.3510.693-0.4500.1640.549-0.0740.6890.6590.7320.6670.784
cpc曝光量0.1270.9521.0000.958-0.331-0.168-0.388-0.267-0.3280.1740.3100.3350.674-0.4670.1510.549-0.1150.6690.6580.7510.6560.780
cpc访问量0.0440.9710.9581.000-0.302-0.198-0.372-0.254-0.3060.1430.3630.3450.698-0.5030.1900.577-0.0360.6910.6820.7510.6830.820
gmvroi-0.464-0.391-0.331-0.3021.0000.6350.4120.3020.9360.0000.055-0.0560.0310.2360.031-0.1190.1350.0330.108-0.2450.100-0.238
下单转换率0.188-0.139-0.168-0.1980.6351.000-0.108-0.1930.5040.1060.2210.1270.2990.3760.1030.0150.0510.3070.241-0.0780.295-0.107
单均gmv-0.285-0.431-0.388-0.3720.412-0.1081.0000.8320.5050.2150.425-0.320-0.5090.133-0.210-0.4260.192-0.507-0.311-0.460-0.381-0.475
单均实收-0.281-0.318-0.267-0.2540.302-0.1930.8321.0000.5240.1260.320-0.311-0.4680.095-0.272-0.4010.139-0.465-0.218-0.394-0.368-0.389
实收roi-0.487-0.401-0.328-0.3060.9360.5040.5050.5241.0000.0000.055-0.127-0.0650.243-0.044-0.1950.101-0.0640.093-0.2880.010-0.284
平台i0.1230.2300.1740.1430.0000.1060.2150.1260.0001.0000.9800.0550.2180.1010.2390.2071.0000.1900.2050.1130.2100.173
平台门店名称0.3400.3690.3100.3630.0550.2210.4250.3200.0550.9801.0000.1580.3490.3990.3330.2990.9840.3360.2790.3320.3030.360
无效订单0.0590.3510.3350.345-0.0560.127-0.320-0.311-0.1270.0550.1581.0000.481-0.1770.2760.433-0.0250.4820.4260.4340.4650.452
有效订单0.0360.6930.6740.6980.0310.299-0.509-0.468-0.0650.2180.3490.4811.000-0.3490.5730.8660.0200.9930.9450.8550.9860.893
自增主键0.213-0.450-0.467-0.5030.2360.3760.1330.0950.2430.1010.399-0.177-0.3491.000-0.142-0.4040.102-0.347-0.350-0.449-0.351-0.504
自然曝光量-0.0990.1640.1510.1900.0310.103-0.210-0.272-0.0440.2390.3330.2760.573-0.1421.0000.7620.0730.5760.5610.6660.5890.567
自然访问量-0.0700.5490.5490.577-0.1190.015-0.426-0.401-0.1950.2070.2990.4330.866-0.4040.7621.0000.0170.8710.8340.8790.8660.912
门店ID-0.019-0.074-0.115-0.0360.1350.0510.1920.1390.1011.0000.984-0.0250.0200.1020.0730.0171.0000.0090.036-0.0640.054-0.006
门店下单量0.0460.6890.6690.6910.0330.307-0.507-0.465-0.0640.1900.3360.4820.993-0.3470.5760.8710.0091.0000.9380.8580.9790.896
门店实收-0.0440.6590.6580.6820.1080.241-0.311-0.2180.0930.2050.2790.4260.945-0.3500.5610.8340.0360.9381.0000.8310.9670.864
门店曝光量0.0040.7320.7510.751-0.245-0.078-0.460-0.394-0.2880.1130.3320.4340.855-0.4490.6660.879-0.0640.8580.8311.0000.8470.943
门店营业额-0.0130.6670.6560.6830.1000.295-0.381-0.3680.0100.2100.3030.4650.986-0.3510.5890.8660.0540.9790.9670.8471.0000.883
门店访问量-0.0500.7840.7800.820-0.238-0.107-0.475-0.389-0.2840.1730.3600.4520.893-0.5040.5670.912-0.0060.8960.8640.9430.8831.000

Missing values

2025-11-04T15:01:50.281366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-11-04T15:01:50.347145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-11-04T15:01:50.435844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

updateTime平台i门店ID平台门店名称日期cpc单次点击费用cpc总费用cpc曝光量cpc访问量gmvroi下单转换率单均gmv单均实收实收roi无效订单有效订单自增主键自然曝光量自然访问量门店下单量门店实收门店曝光量门店营业额门店访问量
02019/12/12 11:54美团8184590蛙小辣火锅杯(合生汇店)2019-12-101.30225.6527111737.430.1757.4819.802.560.059.015016031427.0159.056.01167.974138.03391.38332.0
12019/12/12 11:54美团8223184蛙小辣美蛙火锅杯(大宁国际店)2019-12-101.54261.1036651694.300.1352.9918.881.530.035.0150160511.086.032.0660.733676.01854.76255.0
22019/12/12 11:54美团8106681蛙小辣·美蛙火锅杯(长风大悦城店)2019-12-101.38177.5021151296.750.1851.4920.382.671.053.01502265874.0165.053.01080.312989.02728.72294.0
32019/12/12 11:54美团8165842蛙小辣·美蛙火锅杯(虹口足球场店)2019-12-101.47240.3029371647.430.1956.3519.252.542.064.01502274614.0162.063.01231.863551.03606.10326.0
42019/12/12 11:54饿了么2001220953利芳·一人食大盘鸡(国定路店)2019-12-101.55623.5041904015.350.1749.6912.711.370.0132.015025231872.0387.0132.01677.966062.06558.49788.0
52019/12/12 11:54饿了么2000555792蛙小辣·美蛙火锅杯(虹口足球场店)2019-12-101.61207.8016281293.170.0956.1018.201.030.032.01502706802.0223.032.0582.442430.01795.34352.0
62019/12/12 11:54饿了么2001104355蛙小辣·美蛙火锅杯(宝山店)2019-12-101.25198.5020431596.520.1364.6525.622.580.054.015027361108.0254.052.01383.313151.03491.02413.0
72019/12/12 11:54饿了么2000507076蛙小辣火锅杯(五角场店)2019-12-101.35166.4017051236.400.1557.8121.282.361.063.015029671470.0284.061.01340.473175.03642.10407.0
82019/12/12 11:54饿了么2001020019蛙小辣·美蛙火锅杯(真如店)2019-12-101.51140.301376934.820.1453.4514.661.320.046.015029871394.0245.046.0674.162770.02458.60338.0
92019/12/12 12:49美团8106681蛙小辣·美蛙火锅杯(长风大悦城店)2019-12-091.40195.3523291406.870.2047.1317.202.513.063.01503654839.0160.061.01083.593168.02969.08300.0
updateTime平台i门店ID平台门店名称日期cpc单次点击费用cpc总费用cpc曝光量cpc访问量gmvroi下单转换率单均gmv单均实收实收roi无效订单有效订单自增主键自然曝光量自然访问量门店下单量门店实收门店曝光量门店营业额门店访问量
11672020/8/2 14:29饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-08-012.2598.90837445.380.2352.4316.751.721.059.052162882428.0203.057.0988.543265.03093.24247.0
11682020/7/16 14:19饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-142.25184.181351825.030.2349.4315.951.621.065.046322422561.0189.062.01036.773912.03212.68271.0
11692020/8/3 14:28饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-08-022.1998.50882455.480.2449.8314.221.561.060.052487022445.0196.058.0853.393327.02989.62241.0
11702020/7/29 14:29饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-282.05211.2718991036.690.2652.7818.102.301.078.050921522060.0193.077.01411.883959.04116.74296.0
11712020/7/21 14:29饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-202.24236.9720591066.600.2951.6617.672.261.073.048447521827.0146.072.01289.923886.03771.52252.0
11722020/9/3 14:33饿了么2001104355蛙小辣·美蛙火锅杯麻辣烫(宝山店)2020-09-021.7232.602511913.440.3860.9320.594.542.027.06408364676.055.028.0555.97927.01645.2274.0
11732020/7/25 14:28饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-242.14175.471126825.600.2448.9715.021.722.057.049698851808.0147.056.0855.862934.02791.10229.0
11742020/7/18 14:28饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-172.23185.101548835.380.2449.9616.891.822.062.047556491795.0167.060.01047.093343.03097.62250.0
11752020/7/28 14:29饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-271.99141.251221716.210.2745.9513.761.862.062.050641321905.0152.060.0853.163126.02848.94223.0
11762020/7/23 14:30饿了么337460136拌客·干拌麻辣烫(武宁路店)2020-07-212.06134.191131656.480.2748.8315.932.112.065.048775192188.0165.063.01035.143319.03173.74230.0